FKIE_CVE-2019-10160
Vulnerability from fkie_nvd - Published: 2019-06-07 18:29 - Updated: 2026-06-17 02:10
Severity
Summary
A security regression of CVE-2019-9636 was discovered in python since commit d537ab0ff9767ef024f26246899728f0116b1ec3 affecting versions 2.7, 3.5, 3.6, 3.7 and from v3.8.0a4 through v3.8.0b1, which still allows an attacker to exploit CVE-2019-9636 by abusing the user and password parts of a URL. When an application parses user-supplied URLs to store cookies, authentication credentials, or other kind of information, it is possible for an attacker to provide specially crafted URLs to make the application locate host-related information (e.g. cookies, authentication data) and send them to a different host than where it should, unlike if the URLs had been correctly parsed. The result of an attack may vary based on the application.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| python | python | * | |
| python | python | * | |
| python | python | * | |
| python | python | * | |
| python | python | 3.8.0 | |
| python | python | 3.8.0 | |
| redhat | enterprise_linux_desktop | 7.0 | |
| redhat | enterprise_linux_eus | 7.6 | |
| redhat | enterprise_linux_server | 7.0 | |
| redhat | enterprise_linux_server_aus | 7.6 | |
| redhat | enterprise_linux_server_tus | 7.6 | |
| redhat | enterprise_linux_workstation | 7.0 | |
| debian | debian_linux | 8.0 | |
| debian | debian_linux | 9.0 | |
| opensuse | leap | 15.0 | |
| opensuse | leap | 15.1 | |
| fedoraproject | fedora | 29 | |
| fedoraproject | fedora | 30 | |
| fedoraproject | fedora | 31 | |
| canonical | ubuntu_linux | 12.04 | |
| canonical | ubuntu_linux | 14.04 | |
| canonical | ubuntu_linux | 16.04 | |
| canonical | ubuntu_linux | 18.04 | |
| canonical | ubuntu_linux | 19.04 | |
| redhat | virtualization | 4.0 | |
| redhat | enterprise_linux | 7.0 | |
| netapp | cloud_backup | - | |
| netapp | converged_systems_advisor_agent | - |
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"tags": [
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],
"url": "https://lists.debian.org/debian-lts-announce/2019/06/msg00022.html"
},
{
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},
{
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},
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{
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{
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{
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{
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},
{
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],
"sourceIdentifier": "secalert@redhat.com",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-172"
}
],
"source": "secalert@redhat.com",
"type": "Secondary"
},
{
"description": [
{
"lang": "en",
"value": "CWE-522"
}
],
"source": "nvd@nist.gov",
"type": "Secondary"
}
]
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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